This is a tutorial style book that will teach usage of Python tools for GIS using simple practical examples and then show you how to build a complete mapping application from scratch. The book assumes basic knowledge of Python. No knowledge of Open Source GIS is required. Experienced Python developers who want to learn about geospatial concepts, work with geospatial data, solve spatial problems, and build map-based applications. This book will be useful those who want to get up to speed with Open Source GIS in order to build GIS applications or integrate Geo-Spatial features into their existing applications.
Python Geospatial Development is a book aimed mainly for Python developers who wish to widen their capabilities to include also geospatial coding. The book is divided in different chapters, all with some python code and therefore functions as a hand-on tutorial. The book begins with some basic information about Python and geospatial development and how to use python when analyzing geospatial data. Next chapter describes some basic GIS concepts such as location, how to calculate distances, problems with different units to be aware of, and how to manage different projections. Since geographical data can be expensive another chapter describes freely available data on the Internet, making it possible for a Python developer to test geospatial coding without having to spend too much money to buy data. As far as I’ve read I agree this is a good book for Python developers, not for those who need to learn Python.
I read this book as a Python developer already working with GIS applications for a few years, to see if there were bits of knowledge I was missing. I learned a few new things, for instance a better understanding of what PyProj is used for, and I have a better overview of the capabilities of different spatial databases.
It's a bit hard for me to judge how good this book is for people without my experience though. I have a feeling that it is mainly a list of a number of libraries and technologies, and some examples, and that it is a bit light on strong opinions and recommendations. I work with raster data a lot, reading the data and doing Numpy calculations on them, and that sort of thing isn't mentioned much. But the book is already quite large so perhaps it's not fair to expect that.
If you are new to doing Python and GIS, then this book is definitely a good overview of the most important libraries, and it will help you get up to speed.
This book provides a nice variety of application areas within the field of GIS. From Coordinate systems to databases, editing to map making, this book has something for everyone. The author provides a large number of code examples which work through many real-world scenarios. The inclusion of Open Source examples is an added bonus. This is a great resource for anyone wishing to advance their skills in Geospatial programming using Python.
This book is well written as a technical user document. I also appreciate that software used is also open source. There are many diagrams to explain items visually. If you would like to use Python and explore GIS concepts, this is an excellent resource with many examples and practices to try out.